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Networks, Emergence, Iteration and Evolution
E:CO Issue Vol. 11 No. 4 2009 pp. 91-98
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Networks, Emergence, Iteration and Evolution
William Chamberlin
Texas Tech University Health Sciences Center, US
Recognition that the reductionist approach to science leaves great gaps in our
understanding has led to the synthesis approach to further explain the world around
us. The synthetic approach examines the
inter-relationships of individual entities as
they interact to create complex networks.
This approach spawned the creation of a
new science—the study of Complex Systems. This article takes the concepts of
Complexity Theory and hypothesizes
a process of simple steps iterated many
times over that explains the emergence of
new entities and the evolution of our Universe. The concept of systems, emergence,
iteration and evolution is proposed to explain the process underlying our evolving
Universe. This process would be expected
to leave fractal patterns in its wake. The
fractal patterns are related to the shared
tendencies for self-organization found in
complex networks. The principles apply
to all networks irrespective of their component parts and include both inanimate
and living systems.
Introduction
W
hat good is a worldview if it does
not explain the events around us in
a meaningful and internally consistent manner that helps us to understand and
resolve the problems that we continually face?
This work proposes a worldview that conceives of everything as a process of interacting
systems acting on hierarchical, evolving levels.
This process is theorized to be fundamental to
the evolution of the Universe. Thus, the Universe is seen as being built out of layers of complex dynamic systems, each layer consisting of
the ‘emergent properties’ that are generated
from the complex interactions of the systems
in the level below it.
The Universe is everything we know
and think—and probably more. It definitely
includes particles, forces, and energy. The subChamberlin
ject matter of physics, chemistry and biology
as well as the abstract notions of forces, ideas
and information are all aspects of the Universe.
A truly universal ‘law’ describing the Universe
must apply to them all. This article discusses a
process that seems to be universal and accounts
for the development and evolution of all that
was—and will be—‘new’ in our Universe.
Hopefully, most of the ideas expressed
in this article are not new. They have already
been developed, discussed and published in
the scientific literature by others. The uniqueness of this article lies in the emphasis on the
relationship of emergence and the iterative
process with the fractal patterns observed
throughout Nature, and proposes that this relationship underlies the evolution of the Universe.
Systems, Networks, Emergent Phenomena,
Iteration and Evolution
A. Single entities (E) interact to form complex
interacting systems. New behavior traits
emerge (emergent phenomena) from the
dynamic interplay of the components of
the system...
B. The newly emerged properties define the
system. The original system may no longer
be viewed as a system, but rather as a single
new unique entity (E1).
C. A detailed description of the characteristics
of this new entity (E1) is a description of
the emergent properties that define it.
A1.Single entities (E1) interact to form complex interacting systems. New behavior
traits emerge (emergent phenomena) from
the dynamic interplay of the components
of the system.
B1.The newly emerged properties define the
system. The original system may no longer
be viewed as a system, but rather as a single
new unique entity (E2).
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C1.A detailed description of the characteristics
of this new entity (E2) is a description of
the emergent properties that define it.
conceived as agents of interaction. The forces
and their carriers of interaction are listed below:
A2.Single entities (E2) interact to form complex, etc., etc., etc.
Strong Force (gluons), Weak Force (bosons),
Electro-magnetic Force (photons) and Gravity
(gravitons?).
The process of smaller systems interacting to create new ‘emergent’ properties
that define new entities—and then these entities forming complex networks out of which
newer ‘emergent phenomena’ arise is hypothesized to be the process by which the Universe
evolved. It is an iterative process. The critical
concept is that all single entities can be viewed
as complex systems composed of their component parts, and these parts may be seen as
smaller systems themselves. Since all single
entities are systems, the identifiable characteristics of any single entity are the emergent
properties that arise out of the interactions of
the ‘lesser systems’ that comprise it.
In summary, a single entity on one level
can be viewed as being the ‘emergent properties’
of a complex dynamic system of smaller entities
existing at a lower level. Looking forward, we
can predict that as our current systems form
modules and interact in complex dynamic
ways, new ‘emergent phenomena’ will arise
and we will evolve, we just cannot predict
what these emergent properties will be.
Systems/Emergence Theory is best explained by example. A very brief description
of the evolution of the Universe will be given
touching on the beginning of the eras of physics, chemistry and biology.
Era of Particle Physics
B
ased on the Standard Theory of Particle Physics it is theorized that by one
trillionth of a second after the Big Bang
fundamental particles were already interacting
with each other in dynamic systems to create
the building blocks of the Universe.
As conceptualized today, there are
two major classes of matter, hadrons and leptons. Hadrons and leptons are distinguished
by their behavior characteristics. They interact
through the four Forces via the exchange of energy quanta. These packets of energy are best
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Hadrons are particles that participate in all four
known types of interactions—strong, weak,
electro-magnetic and gravitational.
Leptons are particles that do not participate in
strong interactions.
Charged leptons participate in 3 interactions—
weak, electromagnetic and gravitational.
Neutral leptons participate in 2 interactions—
weak and gravitational.
Leptons are considered to be fundamental particles.
Hadrons are composed of the fundamental particles called quarks and gluons. Combinations
of the six different ‘flavors’ of quarks produce
hadrons with different properties (protons,
anti-protons, neutrons, pi-mesons, k-mesons
etc.).
“The quarks inside a baryon or meson (types of
hadrons) are continually interacting with one
another via the strong force field. At any instant
in time, they may contain many virtual particles: gluons and additional quark/anti-quark
pairs. The picture of a proton as made of three
quarks is thus a gross simplification. For example, we know from measurements that in a high
momentum proton only about half the momentum is carried by quarks, the rest is carried by
gluons” (www2.slac.stanford.edu).
Paraphrasing the above in systems/
emergence terminology: the six different flavors of quarks and gluons interact to form
dynamic systems of interacting fundamental
particles. These dynamic networks develop behavior characteristics that we recognize as the
various types of hadrons—protons, anti-proE:CO Vol. 11 No. 4 2009 pp. 91-98
tons, neutrons, anti-neutrons etc. The emergent characteristics define and become the particles of the Universe.
As the Universe expanded and the temperature cooled, hadrons (protons) and leptons (electrons) formed systems that displayed
the emergent properties that we recognize as
hydrogen atoms. Under the influence of gravity, hydrogen atoms coalesced to form stars.
Conditions were suitable in these stars for hydrogen atoms to interact with each other, and
out of these interactions came new systems of
fused nuclei with the emergent qualities of the
heavier elements.
In short, out of the interacting systems
of quarks and gluons emerged protons, from the
interactions of protons and electrons emerged
hydrogen atoms, and in the furnaces of stars the
hydrogen atoms formed systems displaying the
emergent properties of the heavier atoms found
in the Periodic Table of the Elements.
The process—of fundamental particles
interacting to form systems from which new
behavior characteristics emerged that in turn
defined new entities—was an ongoing process
from the very beginning.
Era of Chemistry
O
nce the formation of atoms has occurred, it is easy to trace the formation of systems of atoms as they form
molecules. Each individual molecule may be
viewed as a system composed of its constituent atoms. And of course, the myriad molecules that are formed interact with each other
to form still larger molecular networks. The
molecular systems manifest emergent properties that possess the attributes of the physical
Universe. Thus the elements and compounds
that form the earth and stars are created. Needless to say, the underpinnings of the chemical
systems are based on the micro-systems of
subatomic particles.
Era of Biology
A
very special branch of chemical evolution involves the complex, adaptive
dynamic systems that are formed from
the chemistry of carbon, hydrogen, oxygen,
nitrogen and other trace elements. At least at
Chamberlin
one site in the Universe C, H, O and N formed
molecules that interacted with one another
in a very special way. Some of the molecules
that were products of chemical reactions in the
network not only served as substrates for additional reactions, but they also served as catalysts for reactions that were involved in their
original synthesis. In this manner reactions
became ‘autocatalytic’ and the systems, when
provided with sufficient substrates, developed
the ability to grow and replicate. As these autocatalytic, self-replicating systems increased in
number, size and complexity they developed
emergent characteristics that we now associate
with Life. Thus, out of ‘emergent chemistry’
came ‘evolutionary biology’.
Under the evolutionary pressures of a
coevolving environment, the systems became
increasingly complex. Molecular pathways
within simple bacteria increased in complexity and altered the phenotypes of the cells in
which the systems were found. Simple prokaryotes developed complex relationships
and became eukaryotes. Single cell eukaryotes
formed systems with the emergent properties
of colonies (sponges). Complex systems built
upon underlying complex systems and the
process continued until multi-cellular plants
and animals with specialized organs evolved.
Skipping forward, it appears that arguably the highest level of systems/emergent
integration found in Nature is the intelligent
self-awareness emerging out of the network of
trillions of interacting neurons in the human
brain. This process continues and the future
will predictably take us to the next level.
The key point is that everything has
evolved by the same process—component
parts interact to form complex systems that
display new characteristics as a result of their
complex interactions. The new and possibly
unique emergent properties define new entities. These new entities may form complex
systems performing on the next ‘higher’ evolutionary level. An iteration of this process explains the evolution of the Universe from its
earliest moments, when all that existed was
energy and a few subatomic particles, to the
present.
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Evidence for Iterative Emergence
T
he proposed iterative process is conceptually possible, but is there any evidence
that the Universe really is built out of
layers of interacting networks? Certainly the
emergence of new entities occurs (the reader is
referred to the numerous publications on this
subject, e.g., Zukav, 1979; Casti 1994; Kauffman, 1995, 2000; Johnson, 2001; Morowitz,
2002; Laughlin, 2005) but does a repetition
of this process account for the construction of
everything in the Universe? Evidence for this
hypothesis may be indirect and somewhat soft
but it is nevertheless intriguing. The iterative
process of interacting networks creating new
entities on the smallest scales of space and
time to the largest may be reflected in the fractal patterns found throughout Nature involving different time and space scales. Somehow
these fractal patterns reflect similar tendencies
for self-organization found in networks of all
sizes as theorized in complexity theory.
Complex Systems as a Science
R
eviewing the essential lessons of the
science of Complexity will be helpful.
There are several key observations that
may not be intuitively obvious.
1. Multi-variable complex adaptive dynamic
systems display similar behavior characteristics. These similarities exist even though
the systems may be composed of different
components. This observation implies that
the interactions of the components possess
an importance independent of the nature
of the components. The study of these similarities is the study of complexity.
2. At a threshold of energy and complexity,
systems develop new behavior characteristics that we call ‘emergent phenomena’.
The emergent traits may be totally unpredictable from what is known about the
component parts. This observation is summarized in the phrase “The whole is more
than the sum of its parts.”
3. Emergent phenomena appear at phase
transitions occurring at the interface of
conditions of extreme stability and conditions of excessive instability. This inter-
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face has been colorfully named the ‘edge
of chaos’. Mathematical models predict
bifurcation patterns—or a doubling- of the
possible semi-stable states that can occur at
these phase transitions.
4. These observations are seen in systems
composed of atoms, or molecules, or cells,
or animals, or neurons, or mixtures of any
independent ‘nodes’ all interacting with
each other.
5. Complex adaptive systems exist in different size scales and interact in different time
scales. This brings us to one last interesting
concept—the concept of fractals.
The science of Physics is built on the
use of mathematical concepts and equations
that construct models of the Universe. The
mathematical concept of ‘fractals’ serves as
a model for the systems/emergence theory.
Fractals are entities that exhibit similar, but not
necessarily identical, traits when examined on
different measurement scales. They are said
to display self-similarity and be invariant under length scale transformation. The wooden
Babushka dolls that open up to reveal similar
dolls within may serve as a concrete analogy.
If our Universe is really built from emergent
traits springing forth from layers of complex
interacting systems and since complex systems all possess similarities, then the concept
of fractals may model the most fundamental
creative process in the Universe.
Mathematical Model for Complex Systems
Behavior and Fractal Geometry
S
ong, Havlin and Makse published a letter
in Nature that is particularly relevant to
the premise put forth in this paper. They
describe a mathematical process by which several different naturally occurring complex systems are shown to display self-similarity or invariance under a length scale transformation.
Their work provides mathematical support for
the idea that the self-similar fractal patterns
found in nature may be related to the processes
of networks and emergence described previously.
Interested readers must read their article but the abstract is as follows:
E:CO Vol. 11 No. 4 2009 pp. 91-98
Complex networks have been studied extensively owing to their relevance to many real
systems such as the world-wide web, the Internet, energy landscapes and biological and social
networks. A large number of real networks are
referred to as ‘scale-free’ because they show a
power-law distribution of the number of links
per node. However, it is widely believed that
complex networks are not invariant or self-similar under a length-scale transformation. This
conclusion originates from the ‘small-world’
property of these networks, which implies that
the number of nodes increases exponentially
with the ‘diameter’ of the network, rather than
the power-law relation expected for a selfsimilar structure. Here we analyze a variety
of real complex networks and find that, on the
contrary, they consist of self-repeating patterns
on all length scales. This result is achieved by the
application of a renormalization procedure that
coarse-grains the system into boxes containing
nodes within a given ‘size’. We identify a power-law relation between the number of boxes
needed to cover the network and the size of
the box, defining a finite self-similar exponent.
These fundamental properties help to explain
the scale-free nature of complex networks and
suggest a common self-organization dynamics
(Song, et al., 2005: 392).
The renormalization procedure that
they use in which large boxes are drawn
around numerous interacting nodes that are
then considered to be a single new node represents the natural phenomena of the creation of
a new entity out of the emergent qualities of an
underlying complex system. The next step in
their renormalization procedure involves connecting the larger boxes with one another to
create a new network. This step represents the
process of new networks that form using the
newly created larger entities. In both cases the
resultant relationship patterns are self-similar
and independent of length-time transformation. Fractal patterns, by definition, display
self-similarity and are independent of lengthtime transformation.
Chamberlin
Complex Adaptive Dynamic Systems in
Biology
M
anifestations of Complexity Theory
may be found throughout biology.
The biosphere itself is a large complex adaptive dynamic system composed of
all the interacting elements that comprise it.
There are many smaller networks participating
in different time and space scales found within
the biosphere. Fractal patterns amongst these
networks are self-evident. Examples are found
in the inter-relationships of species within the
global animal kingdom, the relationships of
individual animals interacting in a defined ecosystem, the relationship of the bacterial microflora of the human colon and, if our hypothesis
is correct, the relationship of key molecules
with each other found in the metabolic pathways of human molecular biology. Similarities
in the interactions of the components of these
complex adaptive systems reflect fundamental
attributes of Emergence and self-organization
of complex adaptive dynamic systems.
Applying Complexity Theory to the
field of human Medicine promises to provide
new insights that may increase our ability to
understand complex disease processes. Biologic networks exist at different levels. Molecules and organelles are the components of
cells, cells are the components of the major organs, and the major organs form a physiologic
network with the emergent properties manifested at the biologic level of the intact animal
(humans). And, of course, individual humans
form sociologic networks.
Health can be viewed as a state where
there is the proper ‘homeostatic’ balance of the
myriad biochemical networks, cellular networks and large organ networks that comprise
the human body. All the involved complex
adaptive dynamic systems are properly functioning around their correct attractors.
Disease, on the other hand, can be conceptualized as occurring when there is some
disruptive influence that deviates the networks away from their homeostatic attractors.
The clinical manifestations of a disease would
be the altered emergent traits generated at the
different biological levels.
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Infection with Hepatitis A Virus (HAV)
serves as a good example. HAV is ingested, absorbed through the intestinal mucosa and travels via the blood to the liver where it adheres
to and invades the liver cell (hepatocytes). The
virus synthesizes molecules that reproduce
itself and also subvert molecular pathways of
the hepatocyte. Homeostasis of the hepatocyte’s molecular systems is perturbed resulting in ‘disease’ at the molecular level resulting
in the emergence of disease traits at the cellular
level. The human immune system has evolved
mechanisms to sense and respond to microbial pathogens. Pattern Recognition Receptors
sense the presence of HAV molecules and alter
the host cell’s genetic networks such that molecular signals (cytokines) are synthesized and
sent to activate the Innate Immune System.
The host’s immune system (organ) is activated
to respond to the viral infection. The immune
system is another complex adaptive dynamic
system. Immune activation can be conceptualized as a perturbation from its normal ‘healthy’
state to one associated with disease. The manufacture of myriad pro-inflammatory cytokines produces effects on the body that are associated with disease, i.e., fever, muscle aches,
fatigue etc.
Thinking in terms of Complexity Theory can provide insight and help us to understand diseases that are currently poorly understood. Crohn’s Disease (CD) is a good example.
CD is an inflammatory disorder of the gastrointestinal system associated with dysregulated
immunity. The etiology of CD is highly controversial. Perhaps the controversy stems as much
from our current linear approach to thinking
about disease causality as from anything else.
Applying Complexity Theory to the way we
think about the multiple factors known to be
associated with CD may simplify the problem
and resolve the controversy.
Linear logic about causality implies
that A causes B causes C etc. and is represented
in Figure 1.
Non-linear approaches are much more
complex and include positive and negative
feedback and feed-forward loops that incorporate multiple variables (see Figure 2). The
Emergent characteristics of a ‘Complexity
Causal Network’ (etiology) may produce sever-
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Figure 1 Current Linear approach to
Causality
Figure 2 Complexity Theory: Causality due to
interactions of multiple variables
al potential outcomes that Complexity Theory
regards as semi-stable states. Such an approach
allows us to conceptualize and comprehend
the interacting influences of many different
variables. Minor variations in any given variable could potentially drastically alter the resultant (semi-stable state) outcome. Thus, an
etiologic agent when introduced into the mix
may result in a disease state in one instance but
may not cause any changes if the conditions are
slightly different.
Factors thought to be associated with
CD include the following: 32 known gene
polymorphisms, prior exposure to other microbes, age, smoking, immune deficiency, use
of corticosteroids, infection with Adhesive Invasive E. coli, infection with Mycobacterium
avium paratuberculosis, other infections, unknown environmental factors.
The insight gained from applying the
principles of Complexity Theory to contemplating the etiology of CD (and other diseases)
is that no single factor is the causative agent;
there must be a critical blend of factors that result in the emergence of a disease that is labeled
as Crohn’s Disease.
E:CO Vol. 11 No. 4 2009 pp. 91-98
Hierarchical Control Networks
“Nothing makes sense in biology except in the
light of evolution”. When thinking about the
evolution of multi-cellular organisms such as
Man it is apparent that a system must have also
evolved that can coordinate and integrate all
the different molecular, cellular and organ activities that occur during life. This control system must be complex, adaptive and dynamic.
It must respond to changes in the internal and
external environment to modify the organisms global response in order to survive. This
system must be hierarchical in that it must
coordinate activities at the local as well as the
global level. Our known evolved hierarchical
control systems are fundamentally molecular.
The nervous system functions via molecular
neurotransmitters, the endocrine system utilizes peptide and steroid hormones to modulate cellular activity throughout the body, and
individual cells communicate on a local basis
with an array of peptide, carbohydrate, lipid
and other molecules that bind to specific receptors or directly modulate enzyme function.
Using the Complexity paradigm to
think about the command and control mechanisms may allow early recognition of some
exciting new research developments. Given
that all evolution is essentially molecular evolution, it is intriguing to think about the family of steroid molecules as playing a key role in
the evolution of an integrating and coordinating hierarchical control system that allowed
the development of higher multi-cellular organisms. Since we have sequenced the human
genome we know that 46 steroid receptors are
encoded within our DNA. Since these receptors have been preserved they must be there
for a reason. We only know what the ligands
are for a small number of these receptors (androgens, estrogens, corticosteroids, mineral
corticoids, Vitamin D and possibly some others). Thus the ligands and function of the majority of these steroid receptors are unknown.
Changing an OH group from any one of the
carbon atoms on the steroid molecule can alter
the binding to a receptor—and elicit profound
down-stream biologic effects. An example
would be the one hydroxyl group that differentiates testosterone from estrogen—and we
Chamberlin
all recognize the biologic effects that occur.
Most importantly, the addition of an OH group
may take only one metabolic step. It is intriguing to think that a mutation in a receptor may
find a possible ligand only one metabolic step
(mutation) away that opens up potential new
pathways for evolution to explore.
If this hypothesis is in fact true (and it
is only a hypothesis), then steroid molecules
may have played a fundamental role in evolution and the current endocrine, paracrine and
autocrine activities of the naturally occurring
steroids may be key to the integration of the
different metabolic pathways in our bodies.
Assuming that this hypothesis is correct, then research and development of steroids may provide mechanisms to modulate
our metabolic pathways in an advantageous
manner. Such research is currently being performed by a California biotech company that
has molecules in clinical trials. If successful,
their endeavors may bring a sea-change to the
field of Medicine. Already their research is
showing promising activity in the areas of immunology, inflammation, cancer, ageing, diabetes and others. The impact on medical care
may surpass that of the entire antibiotic era—
which of course only addressed infectious
agents.
Applicability
S
o, even if this theory on the evolution
of the Universe is correct, what good is
it for us? It does not change anything;
things are what they are regardless of how they
got there. How does it help? There are two immediate answers to these questions. First, we
have always sought to understand what things
are, how they came to be and why they are what
they are. Perhaps Systems-Emergence Theory
can help answer these questions. Secondly,
employing the systems-emergence approach
may be a practical method for resolving problems. Perceiving things as being constructed
of layers of interacting systems may provide
insight into problems that still confuse us.
Confusion often arises because it is unclear on
which ‘level’ a given variable is functioning.
Insight may be achieved by realizing that ‘reality’ is constructed from layers of complex sys-
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tems. The concept of modules and new entities
are related.
Summary
S
ystems/emergence theory emphasizes
the importance of networks of interacting entities out of which new properties
(entities) emerge. This process is fundamental
to the creation and evolution of all things in the
Universe. It is consistent with current theories
of physics, chemistry and biology.
Acceptance of systems/emergence
theory does not change a thing; things are what
they are. But, an appreciation of the systems/
emergence perspective may provide insight
into the World around us and help us to resolve
paradoxes and problems that we continually
encounter. Utilization of this paradigm may be
particularly useful when contemplating the relationships of the many networks found in the
pyramidal levels of biological systems. This
model allows us to more easily integrate our
knowledge of molecular phenomena with cellular, organ and global function. It also allows
medical scientists and physicians to better conceptualize the dynamic interactive relationships of the multiple factors that are involved
in complex disease processes. Phenotypes are
simply ‘emergent traits’ of underlying genetic,
biochemical and cellular networks. Disturbances in these networks by whatever mechanism at any level may disturb the homeostatic
balance, alter the emergent characteristics, and
manifest as disease.
Song, C., Havlin, S. and Makse, H. (2005). “Selfsimilarity of complex networks,” Nature, ISSN
0028-0836, 433, 392-395.
Zukav, G. (1979). The Dancing Wu Li Masters: An Overview of the New Physics, ISBN
9780060959685 (2001).
William Chamberlin M.D., FACG is currently a member of the medical faculty at Texas
Tech University Health Sciences Center in El
Paso, Texas. He received his undergraduate
education at Dartmouth College and Medical
degree from Tufts Medical School. He is currently involved in an international project addressing and refining the concept of Causality
in Complex Adaptive Systems.
References
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9780060925871 (1995).
Johnson, S. (2001). Emergence: The Connected
Lives of Ants, Brains, Cities and Software, ISBN
9780684868769 (2002).
Kauffman, S. (1995). At Home in the Universe: The
Search for the Laws of Self-Organization and Complexity, ISBN 9780195111309 (1996).
K au ffman , S . (2000). Inves tigations, I SBN
9780195121056 (2002).
Laughlin R.B. (2005). A Different Universe: Reinventing Physics from the Bottom Down, ISBN
9780465038299 (2006).
Morowitz, H.J. (2002). The Emergence of Everything: How the World Became Complex, ISBN
9780195173314 (2004).
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